According to OpenAIDevs on X, introducing WebSockets to the OpenAI Responses API yields about 30% faster rollouts for agentic workflows in Codex-style tooling scenarios, enabling low-latency, long-running agents with heavy tool calls. As reported by OpenAIDevs, the WebSocket mode maintains a persistent, bidirectional channel that reduces HTTP overhead and accelerates function-calling loops, streaming events, and tool invocation round-trips. According to Greg Brockman, this performance gain targets production agent frameworks where iterative tool use dominates latency, offering developers measurable speed-ups, lower infrastructure costs, and improved user responsiveness. As documented on developers.openai.com, the guide positions WebSockets as the recommended transport for high-frequency tool calling, enabling real-time streaming of model outputs, function call arguments, and tool results for end-to-end latency reduction.

According to ElevenLabs (@elevenlabsio), the company has launched built-in test scenarios for their AI agents aimed at improving success rates across key functionalities, including tool calling, human transfers, complex workflows, guardrails, and knowledge retrieval (source: https://twitter.com/elevenlabsio/status/1965455063012544923). This development enables businesses to rigorously validate and optimize their AI agent performance before deployment, reducing operational risks and ensuring more reliable automation in customer service and workflow automation use cases. The feature addresses a critical market need for quality assurance in AI-driven solutions, supporting companies seeking to scale AI adoption with confidence.